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Uncertainty and sensitivity analysis in quantitative pest risk assessments; practical rules for risk assessors

by: Makowski, David

Publication date: 2013-9-13
Usage: Attribution 4.0 International
Topics: Model, Pest risk assessment, Sensitivity, Uncertainty
Publisher: Pensoft Publishers
Collection: biodiversity
Contributor: Pensoft Publishers
Language: English
Rights: https://biodiversitylibrary.org/permissions
Rights-holder: Copyright held by individual article author(s).
Volume: 18
Item Size: 15.3M

Abstract: Quantitative models have several advantages compared to qualitative methods for pest risk assessments (PRA). Quantitative models do not require the definition of categorical ratings and can be used to compute numerical probabilities of entry and establishment, and to quantify spread and impact. These models are powerful tools, but they include several sources of uncertainty that need to be taken into account by risk assessors and communicated to decision makers. Uncertainty analysis (UA) and sensitivity analysis (SA) are useful for analyzing uncertainty in models used in PRA, and are becoming more popular. However, these techniques should be applied with caution because several factors may influence their results. In this paper, a brief overview of methods of UA and SA are given. As well, a series of practical rules are defined that can be followed by risk assessors to improve the reliability of UA and SA results. These rules are illustrated in a case study based on the infection model of Magarey et al. (2005) where the results of UA and SA are shown to be highly dependent on the assumptions made on the probability distribution of the model inputs.
Addeddate: 2025-04-02 19:19:23
Bhl_virtual_titleid: 210923
Bhl_virtual_volume: v.18 (2013)
Call number: 10_3897_neobiota_18_3993
Call-number: 10_3897_neobiota_18_3993
Foldoutcount: 0
Genre: article
Identifier: uncertaintysens18mako
Identifier-ark: ark:/13960/s2x8hvg4tzb
Identifier-bib: 10_3897_neobiota_18_3993
Identifier-doi: 10.3897/neobiota.18.3993
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Pages: 15
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Possible copyright status: In copyright. Digitized with the permission of the rights holder.
Ppi: 300
Source: NeoBiota 18
Year: 2013